Krea 3 vs Grok Imagine Image 2.0: One Model Has an Elo, the Other Has a Stopwatch

There is a head-to-head table you can build for K​rea 3 and G​rok Imagine Image 2.0, and then there is the one that actually exists. G​rok Imagine Image 2.0 has been measured: x​AI's editor, released 7 August 2026, sits at 1,110 Elo on the Artificial Analysis image-editing leaderboard — thirteenth of the ranked models, on 7,792 blind comparisons, at a listed $60 per 1,000 images. K​rea 3, released 15 October 2026, has been measured by nobody. It arrives with a vendor stopwatch — under 8 seconds per edit at native 2K for $0.06 — and no third-party number of any kind. So this is less a contest between two editors than a choice between two kinds of evidence.

Both halves of that contrast are true and neither cancels the other. An Elo tells you what a crowd prefers when it cannot see the label; it cannot tell you whether your logo survived the edit. A latency figure tells you what the vendor's own infrastructure did on the vendor's own prompts; it cannot tell you whether the model is any good. Reading them together is the only honest way to choose, and it is what the rest of this piece does.

What each one is, in the vendor's own words

G​rok Imagine Image 2.0 is positioned by x​AI as an editing environment rather than a one-shot generator, and its feature list reads like one: Magic Wand for region-level edits, segmentation for precise region selection, background removal, multi-image input, a Smart Resize that recomposes one image into nine aspect ratios by inventing new frame content rather than cropping, and templates for product photography, headshots, e-commerce listings, game assets and marketing posters. It is the default Quality Mode on grok.com/imagine and on mobile. The API additionally exposes aspect ratio — including 21:9 and 5:2, both new with 2.0 — resolution, and a low/medium/auto quality parameter.

K​rea 3 is narrower and stranger. It is an editor with no generator story attached: region-scoped changes in a drawn box, character consistency across a sequence, up to six references on the launch post and eight on the product page, native 2K, and a voice-note workflow in the app where you speak an instruction and get the edit back. Where G​rok ships named tools and presets for verticals, K​rea ships one mechanism — find the region, render only that — and a speed claim.

• Released — K​rea 3: 15 October 2026. G​rok Imagine Image 2.0: 7 August 2026.

• Independent editing rank — K​rea 3: unranked, no entry. G​rok Imagine Image 2.0: #13 at 1,110 Elo on 7,792 samples, per Artificial Analysis.

• Price — K​rea 3: $0.06 per image at 2K, $0.03 at 1K, flat. G​rok Imagine Image 2.0: from $0.04 per image, billed at the quality tier actually served; the board's representative figure is $60 per 1,000.

• Speed — K​rea 3: under 8 seconds end to end at 2K, vendor-stated. G​rok Imagine Image 2.0: no figure from x​AI and no independent measurement; the only seconds-per-edit number we can find for it is K​rea's own, at 19 seconds, which is a competitor's measurement on a competitor's traffic.

• Resize and reformat — K​rea 3: not a documented workflow; edits are region-scoped. G​rok Imagine Image 2.0: Smart Resize across nine aspect ratios, recomposing rather than cropping.

• Multi-image input — K​rea 3: 6 or 8 depending which K​rea page you read. G​rok Imagine Image 2.0: five source images per edit, per current documentation, up from the three the API capped at launch.

• Weights — neither. No open weights on either side; both are hosted models.

Reading a rank of thirteen

The temptation with an Elo is to treat the number as a verdict. It is more useful as a map of where the disagreements are.

On the Artificial Analysis image-editing board, G​rok Imagine Image 2.0 sits at 1,110 Elo across 7,792 blind comparisons, listed at $60 per 1,000 images. For scale, the top of that same board is O​penAI's G​PT Image 2.5 Sunburst at 1,198 on a stated interval of 1,187 to 1,209, its Flare sibling at 1,177, and a tie for third between Nano Banana 2.1 and M​icrosoft's MAI-Image-2.6 at 1,148. Those gaps are wide relative to the intervals — Sunburst to G​rok is 88 Elo — but they say nothing at all about latency, and G​rok's entry carries less than half of Sunburst's sample count.

Two caveats to hold. The board lists G​rok's creator as S​paceXAI, which is a housekeeping detail worth knowing before you search for the row and fail to find it. And the rank is board-specific in a way that matters here: the same model sits fifth on the text-to-image board at 1,166 Elo, and thirteenth on editing at 1,110. If you are buying an editor, the editing row is the one you are buying, and it is the lower of the two.

The sharper version of that comes from the tier it replaces. The older grok-imagine-image-quality slug still sits on the editing board at 1,091, nineteenth place, so on editing the new tier is ahead of the old one by roughly nineteen Elo, for a $0.01-per-image premium. On text-to-image the same generational step was worth well over a hundred. x​AI shipped a much better generator and a modestly better editor, and only one of those improvements would have led a launch post.

And G​rok's independent reputation to date is uneven in a specific way: in a six-prompt, single-seed comparison against gpt-image-2 we covered previously, x​AI's model led clearly on photorealism and identity retention — correct portrait anatomy, pore-level skin detail, natural catchlights — and lost on production-critical behaviour, rendering Traditional Chinese characters when asked for Simplified in a film-poster headline, and returning a photorealistic image with only a light painterly pass when a watercolour style fusion was requested. That is one small test, not a body of evidence, and we said so at the time. But the failure it found — multilingual text compliance — is the kind that takes a localisation pipeline down, and no Elo average will ever surface it.

K​rea 3 has no equivalent record in either direction. It is four days old, has no board entry, and the only third-party signal attached to it is a customer testimonial: Pixelcut's co-founder and CEO, quoted by K​rea, saying his team ran early checkpoints in front of paying users and that lighting on product shots was the standout. Useful, unverifiable at our end, and labelled here as a partner statement.

The feature gap that matters more than the price gap

On paper the prices are close: six cents against a "from $0.04" that rises with the quality tier actually served. The difference is not the cents. It is what each model is willing to do to your frame.

G​rok Imagine Image 2.0 will reformat. Smart Resize invents new content to turn one image into nine aspect ratios rather than cropping, which is exactly what an ad team needs when the same hero has to run at 1:1, 9:16 and 2:1. It will also composite up to five sources into one edit. K​rea 3 will not do either, as documented — its pitch is the opposite discipline. Draw a box, describe the change, and everything outside the box stays where it was, with precision defined as the share of pixels outside the edit area left unchanged, compared at quarter resolution after alignment.

Those are complementary, not competing, and the cost of choosing wrongly is asymmetric. A marketing team that buys K​rea 3 for a reformatting workflow gets a model that is excellent at a job it was not asked to do. A catalogue team that buys G​rok Imagine Image 2.0 for label-accurate product edits gets a very capable editor with no published containment metric — and possible multilingual text risk on top, per that one test.

Cost at catalogue scale, with both caveats attached

For K​rea 3 the arithmetic is trivial and the risk is that it is the only arithmetic available. 100,000 edits at $0.06 is $6,000, and K​rea's own FAQ says the launch price is the list price, not a subsidy, and that it expects the price to fall rather than rise. That is a vendor statement about the future, so a budget built on it is a bet.

For G​rok Imagine Image 2.0 the shape is different, and there is a deadline hiding in it. The model bills from $0.04 per image at the quality tier actually served, and the default when you omit the parameter is auto — which currently serves low for generation and medium for editing, so the same request can bill differently depending on which path the service picks. Pinning the tier makes the bill predictable. Meanwhile the older grok-imagine-image-quality slug, at $0.05 per image, retires on 2 November 2026 after a 60-day notice; from that date it keeps resolving but requests are served by G​rok Imagine Image 2.0 at low quality. Teams that change nothing see a price drop and a silent change in output quality, which is the worst of both — unless you read the model field in your responses. That retirement schedule is x​AI's own documentation, not something anyone has independently verified.

Where both sit, and how to hold them

Neither model is one you should wire directly into a customer-facing pipeline this month. One has a leaderboard rank, a retired slug underneath it and a documented multilingual text failure; the other has a price, a stopwatch and no external evidence of any kind. The reasonable posture for both is trial behind a fallback.

That is the specific thing routing buys you here, and it is worth being precise about what we do and do not cover. OrcaRouter provides one OpenAI-compatible endpoint across a few hundred models with provider list prices passed through at no markup — a vendor price cut reaches your bill the same day — plus failover that sends a provider error or rate limit to a fallback rather than into your batch. On availability: our catalogue carries x​AI's grok-imagine-image line and its model page is live, but the newest G​rok Imagine Image 2.0 tier is a separate entry, so check the current model list rather than assuming the 2.0 quality mode is routable today. K​rea 3 is not routed by us at all. What the endpoint does cover is the rest of the comparison set — G​PT Image 2 and the image models you would benchmark either of these against — so the test you should be running is one configuration, not three integrations.

How to decide, given the evidence is lopsided

If you need an editor with a public, crowd-measured quality position today, that is G​rok Imagine Image 2.0, and you should go in knowing it is ranked eleventh rather than first, that its bill moves with the quality tier unless you pin it, and that its slug-level migration has a date on it. Read the model field in your responses and migrate the retiring quality slug before 2 November 2026.

If you need flat pricing, contained edits and the shortest wall-clock time anyone in this category has published, that is K​rea 3 — with the understanding that you are the first person testing it, that its reference count is documented two ways, and that its identifier appears as K​rea 3 Beta in K​rea's own plan tables.

The tie-breaker is not the model. It is which of the two failure modes you can afford: an edit that takes forty seconds and surprises you on localisation, or an edit that comes back in eight seconds and has never been judged by anyone but its maker. Run forty of your own images through both, and let the answer be yours rather than either vendor's.

For a model whose failure modes are still undocumented, the useful counterpart is the record of what has already gone wrong elsewhere: the documented AI incidents and agent failures around models in this class are collected in the OrcaRouter AI Incident Archive, where each entry carries its own sources, severity, confidence grade and disputed flag.